/*
 *   This program is free software: you can redistribute it and/or modify
 *   it under the terms of the GNU General Public License as published by
 *   the Free Software Foundation, either version 3 of the License, or
 *   (at your option) any later version.
 *
 *   This program is distributed in the hope that it will be useful,
 *   but WITHOUT ANY WARRANTY; without even the implied warranty of
 *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *   GNU General Public License for more details.
 *
 *   You should have received a copy of the GNU General Public License
 *   along with this program.  If not, see <http://www.gnu.org/licenses/>.
 */

/*
 * NaiveBayes.java
 * Copyright (C) 2004-2012 University of Waikato, Hamilton, New Zealand
 * 
 */
package weka.classifiers.bayes.net.search.fixed;

import weka.classifiers.bayes.BayesNet;
import weka.classifiers.bayes.net.search.SearchAlgorithm;
import weka.core.Instances;

/**
 * <!-- globalinfo-start --> The NaiveBayes class generates a fixed Bayes
 * network structure with arrows from the class variable to each of the
 * attribute variables.
 * <p/>
 * <!-- globalinfo-end -->
 *
 * <!-- options-start --> <!-- options-end -->
 * 
 * @author Remco Bouckaert
 * @version $Revision$
 */
public class NaiveBayes extends SearchAlgorithm {

    /** for serialization */
    static final long serialVersionUID = -4808572519709755811L;

    /**
     * Returns a string describing this object
     * 
     * @return a description of the classifier suitable for displaying in the
     *         explorer/experimenter gui
     */
    public String globalInfo() {
        return "The NaiveBayes class generates a fixed Bayes network structure " + "with arrows from the class variable to each of the attribute " + "variables.";
    }

    /**
     * 
     * @param bayesNet
     * @param instances the instances to work with
     * @throws Exception if something goes wrong
     */
    public void buildStructure(BayesNet bayesNet, Instances instances) throws Exception {
        for (int iAttribute = 0; iAttribute < instances.numAttributes(); iAttribute++) {
            if (iAttribute != instances.classIndex()) {
                bayesNet.getParentSet(iAttribute).addParent(instances.classIndex(), instances);
            }
        }
    } // buildStructure

} // class NaiveBayes
